Frontier Technology

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Frontier Technology Inc. (FTI) is seeking an AI/ML Software Engineer to design, build, and deploy secure, scalable software and data systems that support mission operations, analytics, and simulation environments. This role is for a hands-on engineer and someone who loves writing code, building systems end-to-end, and solving real-world technical challenges in secure, distributed environments. Responsibilities - Software Design & Development - Design and implement APIs, data pipelines, and simulation runtime logic that connect and enable mission applications. - Develop software using modern programming languages such as Java, Python, C++, or TypeScript/Angular. - Write clean, testable, and maintainable code following secure coding and software engineering best practices. - Build and integrate modular microservices to improve scalability, maintainability, and interoperability. - Cloud & Containerized Environments - Build and deploy containerized, cloud-native services using Docker, Kubernetes, and CI/CD pipelines (GitLab, Jenkins, or equivalent). - Implement Infrastructure-as-Code and automation scripts to accelerate deployment and configuration management. - Contribute to secure deployments across hybrid or disconnected environments (IL4–IL6, AWS GovCloud, or on-prem). - Systems Integration & Distributed Computing - Develop distributed systems and data integration frameworks using message buses such as Kafka or Redis. - Engineer data flow between analytic, AI, and simulation components to support real-time mission use cases. - Collaborate with system engineers and architects to ensure interoperability across software ecosystems. - Data & Analytics Integration - Build and manage databases (PostgreSQL, MongoDB, graph DBs) and model complex data relationships. - Develop data services that feed analytics pipelines or integrate AI/ML outputs into runtime systems. - Work with serialization and exchange formats such as JSON, Protobuf, GeoJSON, or KML. - Security, Testing & Sustainment - Write, test, and deploy software within secure or classified environments. - Automate testing and monitoring to ensure performance, reliability, and repeatable deployments. - Support the transition of prototypes to operational systems, focusing on maintainability and observability. Qualifications - Must be a U.S. citizen and be willing to obtain and maintain a security clearance, as needed. - 6-10+ years of professional software engineering experience. - 3+ years of professional experience with DevSecOps, Zero-Trust, or ATO/RMF processes in Department of Defense (DoD/DoW) environments. - Strong full-stack or systems engineering background. - Proficiency in one or more of the following languages: Java, Python, C++, or TypeScript/Angular. - Experience building containerized, cloud-native solutions using Docker, Kubernetes, and CI/CD pipelines. - Complete understanding of distributed systems and message buses (Kafka, Redis, etc.). - Experience developing or integrating analytics and AI models into production systems. Preferred Qualifications - Experience deploying code in IL4–IL6 or edge/disconnected environments. - Familiarity with databases such as PostgreSQL, MongoDB, or graph databases. - Knowledge of Infrastructure-as-Code (Terraform, CloudFormation, or CDK). - Bachelor’s degree in Computer Science, Software Engineering, or a related technical field. - Active Secret clearance preferred; ability to obtain one is required.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description FTI is seeking a Distinguished AI/ML Engineer to serve as a technical leader, architect, and integrator — designing, building, deploying, and sustaining AI systems that transform complex mission data into trusted, explainable insights. This is a hands-on builder role, not an analytics management position. The ideal candidate is equally comfortable writing model code, standing up ML pipelines, and integrating AI inference services into operational systems within secure environments. The right candidate blends deep AI/ML engineering expertise with system-level architecture leadership and an ability to unify data engineering, simulation modeling, and responsible AI principles into scalable, mission-ready capabilities. Responsibilities - Architect and integrate hybrid AI systems that combine traditional machine learning, deep learning, large language models (LLMs), and retrieval-augmented generation (RAG) pipelines. - Design and deploy scalable AI architectures including APIs, microservices, and model-serving frameworks that integrate seamlessly with analytic, simulation, or operational systems. - Lead the full AI/ML lifecycle — from data ingestion and feature engineering through training, deployment, and sustainment within secure DoD environments (IL5/IL6, ATO, GovCloud). - Engineer event-driven data pipelines and feature stores for both structured and unstructured data, including text, imagery, and simulation outputs. - Ensure Responsible AI practices by embedding traceability, explainability, and confidence scoring into deployed systems. - Implement and maintain MLOps pipelines (MLflow, Kubeflow, Airflow, Docker/Kubernetes) to support continuous integration, retraining, and drift detection. - Transition R&D prototypes into production, optimizing for mission constraints such as limited compute, edge environments, or disconnected operations. - Provide technical leadership and mentorship, setting standards for model quality, architectural design, and ethical AI deployment across programs. - Collaborate across engineering, data, and modeling teams to unify FTI’s AI portfolio, ensuring interoperability and reuse across mission systems. - Support proposal and solution development, providing technical inputs for AI/ML architectures, data strategies, and Responsible AI assurance frameworks. Qualifications - Preferring candidates close to Dayton OH, Chesapeake VA, Huntsville AL, or Colorado Springs CO. Or willing to travel to these locations and customer sites, as needed. - Bachelor’s degree in Computer Science, Engineering, or a related technical field (Master’s or Ph.D. preferred). - 10+ years of overall experience in AI/ML development, with 5+ years designing and deploying scalable AI/ML architectures, including at least two full lifecycle implementations (from prototype to operational system). - Proficiency in Python, PyTorch, TensorFlow, and modern ML frameworks. - Experience designing or deploying systems using vector databases (Milvus, Pinecone, Weaviate), knowledge graphs, and semantic search frameworks. - Proven ability to design event-driven data pipelines using Databricks, Spark, Flink, or Kafka. - Demonstrated experience deploying AI/ML systems in secure, classified, or edge environments. - Familiarity with Responsible AI and assurance principles, including bias detection, explainability, human-machine teaming, and hallucination prevention. - Experience integrating AI models into simulation, modeling, or operational planning systems is highly desirable. - Experience transitioning R&D systems into accredited production environments. - Active Secret clearance required; TS/SCI strongly preferred. - Strong communication and mentoring skills, with the ability to lead technically while remaining deeply hands-on.